• Journal of Fashion Business
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• v.4 no.4
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• pp.135-151
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• 2000

The porpose of this research is helping product developments and establishment men's marketing strategies. This contents are divided into two parts; the dress shirt's wearing condition and the dress shirt's buying condition. The subjects of the research were male that aged 25-50 and their company is resided in Seoul. The conclusion of this research is summarized as below ; 1. Many consumers have wrong term recognition of dress shirt. Most of men know their dress shirt's sizing designation as casual method(ex, $\cdots$95, 100$\cdots$). Therefore it is happened fitness complains. Dress shirt's wearing frequency for a week is 1-2 days or 5days mostly. A number of dress shirt’s wearing period for one is 6-12 months. Dress shirt‘s wearing frequency fand wearing period varies according to their age, unmarried or married situation, scholarship, occupation. So the manufacturer of men's dress shirt grasps the factor's for their character. 2. The conclusion of dress shirt's buying motivation is need better than impulse buying. If company planning season event, the selling will be improved. Most of men buy their dress shirt by themselves. It means a lot of men are interested in their clothes comparing to old days. And men's favorite purchase place is a department store and agent. when they purchasing, the color and size is very important factor. But dress shirt's sizing designation is not yet established. Therefore the dress shirt's sizing designation is needed as possible.

• Journal of Digital Convergence
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• v.12 no.11
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• pp.233-239
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• 2014

Ultra high-resolution content, the file size is very large, therefore existing encoding techniques, it is not possible to transmit via the network. Efficient use of the network encoder HEVC corporation can be transferred. Compression requires a lot of time because it requires a distributed transcoding system. Distributed transcoding system is a distributed data store, and then encoded using a large number of nodes. The disadvantage of distributed transcoding system for distributed information is exposed or vulnerable to attack by internal managers. In this paper, when the super high definition content transcoding, distributed transcoding system does not guarantee the confidentiality of the problem to solve. We are using SNA, HEVC encoded content data encrypted using the secret distributing scheme was. Consequently, secure shared transcoding is possible, the internal administrator could prevent the attack.

• The Research Journal of the Costume Culture
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• v.16 no.3
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• pp.444-460
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• 2008

The purposes of this study were to investigate life style and various clothing purchasing behaviors of female consumers, and to analyze the differences of life style and clothing purchasing behaviors by 3 age groups(adolescence, middle age, and senescence). The subjects were 750 adult women aged from twenties to sixties who live in Daejeon and Chungnam province. The research method is a survey and research instruments consisted of life style questionnaire, clothing purchasing behaviors questionnaires, and demographic attribution. Data were analyzed by factor analysis, variance analysis, Duncan's multiple range test and $X^2$ test, using SPSS program. The research results are follows. First, 6 factors were emerged in life style(appearance-oriented, achieve-oriented, social life-oriented, economic- oriented, equality of sexes-oriented, and leisure- oriented). Second, 5 factors were emerged in shopping orientation(resonable shopping, conspicuous shopping, voluptuous shopping, devoted shopping, and convenient shopping). Third, clothing purchasing behaviors of adult women showed many differences by age groups. Adolescence women considered more criterion including design, price, and color or pattern, purchased their clothing by psychological reason such as fashion change, and used internet as important source of clothing, whereas senescence women purchased by physical reason such as body size change and functional trouble, used friend and sales person as important source of clothing, and purchased clothing at department store and old style market.

• Proceedings of the Korean Vacuum Society Conference
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• 2013.02a
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• pp.631-631
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• 2013

Battery has major drawbacks including its size and life expectancy, and environmental problem. As an alternative, energy harvesting is emerging as a potential solution to replace battery along with more energy-efficient IT devices. The idea of harnessing energy from our living environment is sustainable, semi-permanent, and eco-friendly. Also, unlike battery, energy harvester does not require much space to store energy. Therefore, energy harvesting can provide a better source of power for small, portable, and wireless devices. Among various ways of harvesting energy from our surroundings, triboelectricity is chosen due to its potential to be miniaturized, and efficient. Triboelectric effect occurs as two different materials with different polarity of charge separation come into contact through friction, and then become separated so that electric potential difference is achieved. In this research, such characteristic of triboelectricity is used as a way to convert ambient mechanical energy into electric energy.Series of recent researches have shown promising results that the triboelectric energy harvester can be simple and cost effective. However, sufficient electricity level required to operate mobile devices has not yet been achieved.In this research, our group focuses on the design and optimization of triboelectric energy harvesting device to enhance its output. By using maskless lithography to pattern Kapton film and silicon substrate, which is used as a mold for PDMS thin layer, and sputtering metal electrodes on each side, we fabricate and demonstrate different designs of triboelectric energy harvester that utilizes the contact electrification between a polymer thin film and a metal thin foil. In order to achieve optimized result, the output voltage and current are measured under diverse conditions, which include different surface structure and pattern, material, and the gap between layers.

• The KIPS Transactions:PartD
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• v.10D no.6
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• pp.1025-1032
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• 2003

Percentiles are convenient measures of the entire range of values of simulation outputs. However, unlike means and standard deviations, the observations have to be stored since calculation of percentiles requires several passes through the data. Thus, percentile (PE) requires a large amount of computer storage and computation time. The best possible computation time to sort n observations is (O($nlog_{2}n$)), and memory proportional to n is required to store sorted values in order to find a given order statistic. Several approaches for extimating percentiles in RS(regenerative simulation) and non-RS, which can avoid difficulties of PE, have been proposed in [11, 12, 21]. In this paper, we implemented these three approaches known as : leanear PE, batching PE, spectral $P^2$ PE in the context of sequential steady-state simulation. Numerical results of coverage analysis of these PE approachs are present.

• The Transactions of the Korean Institute of Power Electronics
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• v.23 no.2
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• pp.77-85
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• 2018

Renewable energy has been increasingly used and widely acclaimed as one of the solutions to rampant environmental problems. Among numerous kinds of renewable sources, the penetration rate of the PV system is relatively higher than that of others due to ease of installation. However, one disadvantage of the PV system is its dependence on weather condition. The PV system is especially critical when it is used for standalone systems because it cannot operate when the power generated from a PV module is not enough. Therefore, PV systems are often used with an energy storage system, such as batteries, to store backup energy when the weather condition is insufficient to supply power to the system. Blackout time can be reduced by increasing the size of the energy storage system, but it is a trade-off with system cost. In this work, optimal sizing of a standalone PV system is proposed to supply power to the system without blackout. The sizing of PV modules and batteries is performed by a simulation based on actual irradiation data collected during the past five years. The Life cycle costing of each system is evaluated to determine an optimal set of PV modules and batteries among several different combinations. The standalone PV system designed by the proposed method can supply power to the system with no interruption as long as the weather condition is similar to those of the past five years.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.4
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• pp.116-123
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• 2009

Feature point matching, which is finding the corresponding points from two images with different viewpoint, has been used in various vision-based applications and the demand for the real-time operation of the matching is increasing these days. This paper presents a real-time feature point matching method by using a local descriptor derived by Zernike moments. From an input image, we find a set of feature points by using an existing fast corner detection algorithm and compute a local descriptor derived by Zernike moments at each feature point. The local descriptor based on Zernike moments represents the properties of the image patch around the feature points efficiently and is robust to rotation and illumination changes. In order to speed up the computation of Zernike moments, we compute the Zernike basis functions with fixed size in advance and store them in lookup tables. The initial matching results are acquired by an Approximate Nearest Neighbor (ANN) method and false matchings are eliminated by a RANSAC algorithm. In the experiments we confirmed that the proposed method matches the feature points in images with various transformations in real-time and outperforms existing methods.

• The Transactions of the Korea Information Processing Society
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• v.1 no.1
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• pp.23-37
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• 1994

In this paper, we design and implement the prototype system, and propose the Extended Faceted Classification. Scheme and the Hybrid Retrieval Method that support classifying the software components, storing in library, and efficient retrieval according to user's request. In order to designs the classification scheme, we identify several necessary items by analyzing basic classes of software components that are to be classified. Then, we classify the items by their characteristics, decide the facets, and compose the component descriptors. According to their basic characteristics, we store software components in the library by clustering their application domains and are assign weights to the facets and its items to describe the component characteristics. In order to retrieve the software components, we use the retrieval-by-query model, and the weights and similarity for easy retrieval of similar software components. As the result of applying proposed classification scheme and retrieval model, we can easily identify similar components and the process of classification become simple. Also, the construction of queries becomes simple, the control of the size and order of the components to be retrieved possible, and the retrieval effectiveness is improved.

• Journal of Service Research and Studies
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• v.2 no.1
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• pp.39-46
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• 2012

It is growing in size of database in companies. This caused to develope data mining techniques to predictive information from the large database. Costs and other effects can give variety of sales exploding through the analysis of the differences. Analysis of the various classification techniques, various angle can be analyzed point of view of the area information. The analysis of rules and patterns associated with a large amount of useful information from the database can be analyzed effectively. Goods store were analyzed using association rules, one of the data mining analysis techniques. Through this type of existing products according to analyze customer buying patterns, data mining has been studied to establish strategic marketing analysis.

• Journal of Digital Contents Society
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• v.16 no.5
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• pp.805-813
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• 2015

Many researchers expect the compressive sensing and sparse recovery problem can overcome the limitation of conventional digital techniques. However, these new approaches require to solve the l1 norm optimization problems when it comes to signal reconstruction. In the signal reconstruction process, the transform computation by multiplication of a random matrix and a vector consumes considerable computing power. To address this issue, parallel processing is applied to the optimization problems. In particular, due to huge size of original signal, it is hard to store the random matrix directly in memory, which makes one need to design a procedural approach in handling the random matrix. This paper presents a new parallel algorithm to calculate random partial Haar wavelet transform based on Single Instruction Multiple Threads (SIMT) platform.